A New Turning Point for Women: Artificial Intelligence as a Tool for Reducing Gender Discrimination in Hiring

Abstract

This paper studies whether firms’ adoption of artificial intelligence (AI) has a causal effect on their probability of hiring female managers. Using panel data on the 500 largest firms, measured by revenues, in Europe and the US, and a two-stage difference- in-differences I find that firms’ use of AI causes, on average, an increase by 3.5% in the hiring of female managers. Exploiting heterogeneity across different types of AI I find that my result is driven by the use of assessment software, rather than that of predictive algorithms. The use of assessment software increases the share of female managers hired by companies and correlates with a reduction in firms being sued for gender discrimination in hiring. Conversely, my findings show that predictive algorithms do not affect gender inequality in managerial hires.

Keywords: artificial intelligence, gender, hiring, discrimination

JEL Classification: J71, M51